Literature DB >> 25570988

USign--a security enhanced electronic consent model.

Yanyan Li, Mengjun Xie, Jiang Bian.   

Abstract

Electronic consent becomes increasingly popular in the healthcare sector given the many benefits it provides. However, security concerns, e.g., how to verify the identity of a person who is remotely accessing the electronic consent system in a secure and user-friendly manner, also arise along with the popularity of electronic consent. Unfortunately, existing electronic consent systems do not pay sufficient attention to those issues. They mainly rely on conventional password based authentication to verify the identity of an electronic consent user, which is far from being sufficient given that identity theft threat is real and significant in reality. In this paper, we present a security enhanced electronic consent model called USign. USign enhances the identity protection and authentication for electronic consent systems by leveraging handwritten signatures everyone is familiar with and mobile computing technologies that are becoming ubiquitous. We developed a prototype of USign and conducted preliminary evaluation on accuracy and usability of signature verification. Our experimental results show the feasibility of the proposed model.

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Year:  2014        PMID: 25570988     DOI: 10.1109/EMBC.2014.6944620

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  SegAuth: A Segment-based Approach to Behavioral Biometric Authentication.

Authors:  Yanyan Li; Mengjun Xie; Jiang Bian
Journal:  IEEE Conf Commun Netw Secur       Date:  2017-02-23

2.  Authentication of Patients and Participants in Health Information Exchange and Consent for Medical Research: A Key Step for Privacy Protection, Respect for Autonomy, and Trustworthiness.

Authors:  Atsushi Kogetsu; Soichi Ogishima; Kazuto Kato
Journal:  Front Genet       Date:  2018-06-01       Impact factor: 4.599

  2 in total

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